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A modular analysis of microglia gene expression, insights into the aged phenotype

BACKGROUND: Microglia are multifunctional cells that are key players in brain development and homeostasis. Recent years have seen tremendous growth in our understanding of the role microglia play in neurodegeneration, CNS injury, and developmental disorders. Given that microglia show diverse functio...

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Autores principales: Cho, Christine E., Damle, Sagar S., Wancewicz, Edward V., Mukhopadhyay, Swagatam, Hart, Christopher E., Mazur, Curt, Swayze, Eric E., Kamme, Fredrik
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6396472/
https://www.ncbi.nlm.nih.gov/pubmed/30819113
http://dx.doi.org/10.1186/s12864-019-5549-9
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author Cho, Christine E.
Damle, Sagar S.
Wancewicz, Edward V.
Mukhopadhyay, Swagatam
Hart, Christopher E.
Mazur, Curt
Swayze, Eric E.
Kamme, Fredrik
author_facet Cho, Christine E.
Damle, Sagar S.
Wancewicz, Edward V.
Mukhopadhyay, Swagatam
Hart, Christopher E.
Mazur, Curt
Swayze, Eric E.
Kamme, Fredrik
author_sort Cho, Christine E.
collection PubMed
description BACKGROUND: Microglia are multifunctional cells that are key players in brain development and homeostasis. Recent years have seen tremendous growth in our understanding of the role microglia play in neurodegeneration, CNS injury, and developmental disorders. Given that microglia show diverse functional phenotypes, there is a need for more precise tools to characterize microglial states. Here, we experimentally define gene modules as the foundation for describing microglial functional states. RESULTS: In an effort to develop a comprehensive classification scheme, we profiled transcriptomes of mouse microglia in a stimulus panel with 96 different conditions. Using the transcriptomic data, we generated fine-resolution gene modules that are robustly preserved across datasets. These modules served as the basis for a combinatorial code that we then used to characterize microglial activation under various inflammatory stimulus conditions. CONCLUSIONS: The microglial gene modules described here were robustly preserved, and could be applied to in vivo as well as in vitro conditions to dissociate the signaling pathways that distinguish acutely inflamed microglia from aged microglia. The microglial gene modules presented here are a novel resource for classifying and characterizing microglial states in health and disease. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12864-019-5549-9) contains supplementary material, which is available to authorized users.
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spelling pubmed-63964722019-03-13 A modular analysis of microglia gene expression, insights into the aged phenotype Cho, Christine E. Damle, Sagar S. Wancewicz, Edward V. Mukhopadhyay, Swagatam Hart, Christopher E. Mazur, Curt Swayze, Eric E. Kamme, Fredrik BMC Genomics Research Article BACKGROUND: Microglia are multifunctional cells that are key players in brain development and homeostasis. Recent years have seen tremendous growth in our understanding of the role microglia play in neurodegeneration, CNS injury, and developmental disorders. Given that microglia show diverse functional phenotypes, there is a need for more precise tools to characterize microglial states. Here, we experimentally define gene modules as the foundation for describing microglial functional states. RESULTS: In an effort to develop a comprehensive classification scheme, we profiled transcriptomes of mouse microglia in a stimulus panel with 96 different conditions. Using the transcriptomic data, we generated fine-resolution gene modules that are robustly preserved across datasets. These modules served as the basis for a combinatorial code that we then used to characterize microglial activation under various inflammatory stimulus conditions. CONCLUSIONS: The microglial gene modules described here were robustly preserved, and could be applied to in vivo as well as in vitro conditions to dissociate the signaling pathways that distinguish acutely inflamed microglia from aged microglia. The microglial gene modules presented here are a novel resource for classifying and characterizing microglial states in health and disease. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12864-019-5549-9) contains supplementary material, which is available to authorized users. BioMed Central 2019-02-28 /pmc/articles/PMC6396472/ /pubmed/30819113 http://dx.doi.org/10.1186/s12864-019-5549-9 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Cho, Christine E.
Damle, Sagar S.
Wancewicz, Edward V.
Mukhopadhyay, Swagatam
Hart, Christopher E.
Mazur, Curt
Swayze, Eric E.
Kamme, Fredrik
A modular analysis of microglia gene expression, insights into the aged phenotype
title A modular analysis of microglia gene expression, insights into the aged phenotype
title_full A modular analysis of microglia gene expression, insights into the aged phenotype
title_fullStr A modular analysis of microglia gene expression, insights into the aged phenotype
title_full_unstemmed A modular analysis of microglia gene expression, insights into the aged phenotype
title_short A modular analysis of microglia gene expression, insights into the aged phenotype
title_sort modular analysis of microglia gene expression, insights into the aged phenotype
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6396472/
https://www.ncbi.nlm.nih.gov/pubmed/30819113
http://dx.doi.org/10.1186/s12864-019-5549-9
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